code: def test_overfit_model_check_no_share_weights(self):
      model = OverfitModel(
          share_implicit_function_across_passes=False,
          coarse_implicit_function_class_type="NeuralRadianceFieldImplicitFunction",
          coarse_implicit_function_NeuralRadianceFieldImplicitFunction_args={
              "transformer_dim_down_factor": 1.0,
              "n_hidden_neurons_xyz": 256,
              "n_layers_xyz": 8,
              "append_xyz": (5,),
          },
      )
      for p1, p2 in zip(
          model.implicit_function.parameters(),
          model.coarse_implicit_function.parameters(),
      ):
          self.assertNotEqual(id(p1), id(p2))
  
      model.to(DEVICE)
      inputs_ = _generate_fake_inputs(2, 80, 80)
      model(**inputs_, evaluation_mode=EvaluationMode.TRAINING)
  
file_path: pytorch3d/tests/implicitron/models/test_overfit_model.py
imports: import unittest
  from typing import Any, Dict
  from unittest.mock import patch
  import torch
  from pytorch3d.implicitron.models.generic_model import GenericModel
  from pytorch3d.implicitron.models.overfit_model import OverfitModel
  from pytorch3d.implicitron.models.renderer.base import EvaluationMode
  from pytorch3d.implicitron.tools.config import expand_args_fields
  from pytorch3d.renderer.cameras import look_at_view_transform, PerspectiveCameras
label_desc: Use image node_id 4 for calling the TestOverfitModel obj's underlying member method code with example usage: obj.test_overfit_model_check_no_share_weights() without return types